July 2013
Volume 13, Issue 9
Free
Vision Sciences Society Annual Meeting Abstract  |   July 2013
The relationship between the local field potential and spiking activity in primary visual cortex
Author Affiliations
  • Adam Kohn
    Albert Einstein College of Medicine
    Speaker
  • Xiaoxuan Jia
    Albert Einstein College of Medicine
    Author
Journal of Vision July 2013, Vol.13, 1387. doi:10.1167/13.9.1387
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      Adam Kohn, Xiaoxuan Jia; The relationship between the local field potential and spiking activity in primary visual cortex. Journal of Vision 2013;13(9):1387. doi: 10.1167/13.9.1387.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

The local field potential (LFP) represents the summed electrical activity in a local region of cortex. It provides a mesoscopic view of network activity and function, between local measures such as single unit spiking activity and more global measures such as BOLD-fMRI and EEG. However, the relationship between the LFP and these signals remains unclear, making it difficult to relate findings across scales of study. We therefore investigated how the LFP is related to spiking activity in primary visual cortex of macaque monkeys, and found a flexible relationship for the gamma frequency components of the LFP. Small sinusoidal gratings, and those masked with noise, induce gamma power that is tuned similarly to spiking activity. Large gratings induce a 'global' gamma rhythm characterized by a distinctive spectral bump. This signal is well tuned for orientation and spatial and temporal frequency, but with a preference that is similar across millimeters of cortex. The preference of this gamma is sensitive to adaptation and the location of a stimulus in visual space. We argue that these properties indicate the global gamma rhythm reflects and magnifies an underlying bias in the neuronal representation of visual stimuli in V1. Our results show that there is not a single, fixed neuronal ensemble contributing to gamma and that the global gamma rhythm may be a useful signal for detecting and characterizing biased representations in visual cortex.

Meeting abstract presented at VSS 2013

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